A MAGDM Model with Multi-granular Probabilistic Linguistic Power

被引：3

作者：

Wang, Juxiang ^{[1
,2
]}

Liu, Yezheng ^{[1
]}

Chen, Xiuming ^{[3
]}

机构：

[1] Hefei Univ Technol, Sch Management, Hefei, Anhui, Peoples R China

[2] Anhui Jianzhu Univ, Sch Math & Phys, Hefei, Anhui, Peoples R China

[3] Fuyang Normal Univ, Sch Comp & Informat Engn, Fuyang, Peoples R China

来源：

2018 5TH INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE AND CONTROL ENGINEERING (ICISCE 2018) | 2018年

基金：

中国国家自然科学基金;

关键词：

multi-attribute group decision making; multi-granular linguistic term set; distance measure; hesitant fuzzy linguistic term set; GROUP DECISION-MAKING; TERM SETS; AGGREGATION; OPERATORS;

D O I：

10.1109/ICISCE.2018.00212

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A novel multi-attribute group decision making (MAGDM) method with multi-granular probabilistic linguistic power is proposed in this paper. Firstly, distance measures between two multi-granular probabilistic linguistic term sets are determined, such as generalized probabilistic linguistic Hamming distance, generalized probabilistic linguistic Euclidean distance, generalized probabilistic linguistic Hausdorff distance, and generalized probabilistic linguistic hybrid approach. To compute the weights of attributes, we propose the cross-entropy method for multi-granular probabilistic linguistic term sets; Secondly, under all the determined distance measures above, a novel MAGDM method is proposed; Finally, four case studies are provided to illustrate the novelty, feasibility, and validity of the proposed MAGMD method.

引用

页码：1030 / 1035

页数：6

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